Landsat 8 Multispectral Analysis

Landsat 8 was successfully launched on February 11 from Vandenberg Air Force Base in California. It initially achieved stable orbit with its sensors turned off. It will gradually be maneuvered into its final orbit before the sensors are completely powered up and testing begins. Landsat 8 is scheduled to start returning large quantities of data (400 scenes per day is the target) in May 2013.

Landsat 8 Specifications

There are a few similarities between Landsat 8 and its predecessor, Landsat 7 and a lot of differences. The biggest difference (a plus for Landsat 8) is that unlike Landsat 7, it works (well, at least we hope it will work properly when powered up). Landsat 7 has a so-called whiskbroom sensor, meaning that it has a small sensor and a mechanical scanning mirror that sweeps from one side of the forward path to the other, successively directing points along the swept path to the sensor. As owners of computer hard drives know, mechanical elements of electronic systems are always the weak link and are prone to early failure. That is what happened to the scanning mirror (actually the scanning mirror corrector called the SLC) in 2003. Since that time Landsat images have black stripes of missing data that must be patched in order to create useful images.

Landsat 8 in contrast has what is sometimes called a push broom sensor. It consists of an array of sensors called a Sensor Chip Assembly (SCA) that each collect data for part of the swath. As a result there are no mechanical parts and this sensor should be much more reliable. The main Landsat 8 SCA is shown schematically below.

The most obvious specificaton difference to the user between Landsat 8 and Landsat 7 is the dynamic range of the digital number (DNs) output from the sensors. Landsat 7 has 8 bits of dynamic range while Landsat 8 has 12. This does not mean that Landsat 8 is more accurate than Landsat 7, or that it can report back a larger number (since any number can be scaled infinitely large). It means that the numbers it returns are known more precisely. Landsat 7 can report 256 discrete levels of sensed electromagnetic radiation (28=256) while Landsat 8 can report 212=4096. Essentially, Landsat 7 measures things with a ruler that has 256 gradients on it while Landsat 8 measures things with 4096 gradients on its ruler. This can theoretically be very useful when trying to determine if one number is different from another, in multispectral signature matching for example. The signal to noise ratio is expected to be much better as well.

What Do These Differences Mean to You?

This increased resolving power comes with a price. Landsat 8 scenes will be considerably larger than Landsat 7 scenes. Landsat 7 scenes can top out at a hefty 710MB or so. Landsat 8 scenes on the other hand will be in the neighborhood of an amazing 1.5GB (unzipped), more than twice as large. This will have a profound affect on everyone involved with Landsat. Users will find that it takes around one hour to download a Landsat 8 scene. The USGS may have to purchase a few extra hard drives at Staples to archive all this data since this will add up to 600GB of new data every day for a scheduled life of five years and probable life of 10 years. (I won't bother to multiply it out, but you get the point). We humble software developers will have to figure out how to manage truly huge data structures using desktop operating systems that are typically limited to 2GB of address space (32 bit Windows systems for example, with half consumed by the operating system). More on this later.

I am skeptical that the increased precision is really worth the computer storage, bandwidth, and re-coding expense not to mention slower processing times. The first problem is that it is wasteful of storage space. Computers process data in increments of 8-bit bytes. Thus, 12 bits of data must be stored in a 16-bit integer data structure, wasting 25% of allocated memory resource. This is expensive indeed if this resource is RAM. My experience with Landsat multispectral analysis is that it is unusual to record two TOA or surface reflectance values that are within 5% of each other even if they represent the same ground feature. Atmospheric distortions, terrain effects and many other factors seem to make the increased Landsat 8 precision somewhat academic. In addition, computer RGB and greyscale models are based on 256 color levels per channel. Since most interpretation of satellite data is visual, the additional computational precision is often lost when the results are displayed using standard 256 bit color models. Increased pixel resolution would have been a far more useful way to spend valuable USGS and user storage and bandwidth resources.

Another reason for the large difference in size between Landsat 8 and Landsat 7 scenes is the number of spectral bands. Landsat 7 has 8 or 9, depending on whether the scene contains one or two versions of the thermal infrared (TIR) band (high gain/low gain). Landsat 8 has two additional multispectral bands, two narrower TIR bands in place of the single Landsat 7 TIR band and a panchromatic band for a total of 11 bands. The two additional bands are a narrow Coastal Aerosol band at a slightly shorter wavelength than the blue band and a Cirrus band sensitive to radiation wavelengths between 1.36 and 1.38 microns.

Another difference between Landsat 8 and its predecessor is the character of the panchromatic band. The Landsat 7 panchromatic band is sensitive to electromagnetic radiation between wavelengths 0.52 to 0.90 microns. This range excludes visible blue but includes the NIR band. It was probably chosen in order to produce a clearer image, since the blue band is most susceptible to Rayleigh scattering than any other. The result however is severe color distortion when the band was used for pan sharpening. It takes a lot of computational effort to correct this and few do it very well. (The PANCROMA™ ELIN algorithm is one of the best for removing such distortions).

The Landsat 8 panchromatic band covers a range of 0.50 to 0.68 microns. This still excludes the blue band but also excludes the NIR band, spanning the visible green and red bands. As a result we can still expect color distortions resulting from pan sharpening, but perhaps not quite so severe as Landsat 7. The band specifications are shown in the table and graphic below.

Finally, the passbands for Landsat 8 bands 5, 6 and 7 are narrower (more discriminating) than the corresponding Landsat 7 bands. This will benefit spectral signature matching and other target discrimination techniques.

Similarities - A Mixed Bag

One of the pleasant similarities between Landsat 8 and Landsat 7 is the file format. It is exactly the same as Landsat 7: uncompressed GeoTiff archived in zip format. Thankfully the USGS fought off suggestions from the engineering department for "improvements" and left the file format alone. Changing formats could have made the transition from Landsat 7 to Landsat 8 considerably more challenging (and expensive) for software developers.

One of the main (disappointing) similarities is the resolution of the panchromatic band. At 15m it is exactly the same as Landsat 7. Those of us who were hoping that the panchromatic sensor would be the same as that on the EO-1 Advanced Lange Imager (10m) that was supposed to be its test bed were sorely disappointed. A higher resolution panchromatic band would have allowed pan sharpening of the multispectral bands up to a more reasonable resolution. Commercial satellite companies may have felt that 10m imagery was getting too close to home and lobbied for the status quo.

Of course the downlink bandwidth requirements would have been greater at the higher resolution. However NASA/USGS could have solved this problem (if it is one) by discarding the least significant four bits of the panchromatic band before downlink. Since the panchromatic band is used mainly for visual effects like pan sharpening there is no point in carrying 12 bits of data for that band. The file size approximately doubles in either case but the users would have been much happier with the higher resolution rather than the greater bit depth for the panchromatic band.

Dealing with the Data Deluge

This leads naturally to the next subject: how will software developers accommodate the new data with its increased bit depth and larger band file sizes. I cannot answer for other developers, but we at PANCROMA™ have developed an approach for the transition to the new data. Some of the key elements are as follows:

Since the new I16 data format closely resembles that already used for Landsat reflectance data published by the USGS in the past, PANCROMA™ can already read the new format and save in the old format. This will be the cornerstone of the transition. Converting from I16 to 8-bit unsigned char format will allow most of the current PANCROMA features to be used with the new data immediately, although at reduced dynamic range.

Some routines like the three band subset, single band subset, vegetation index routines and others have already been modified to accommodate the new I16 format.

The Spectral Analyzer routines have been modified but are awaiting the Landsat 8 calibration data so that the DNs can be converted to TOA reflectances. Other routines are queued for conversion.

Some routines will not be modified. Pan sharpening, histogram matching, etc for example are done for qualitative visual rather than analytical purposes. Since computer RGB color display models can only accept 8 bits per channel it would not make sense to convert these. Gap filling is only used for Landsat 7 data so these will not be converted either.

We expect to have the conversions completed by the time that Landsat 8 data becomes available in May 2013.

Landsat 8 presents both opportunities and challenges both for users and for software developers. Close cooperation among the developer community, the USGS and most importantly Landsat users will be the most important factor determining how smoothly and successful the transition goes. Please contact me using any of the contact information at the PANCROMA™ website for comments, suggestions or questions.